Deep learning models with convolutional and recurrent networks are now ubiquitous and
analyze massive amounts of audio, image, video, text and graph data, with applications in …

Program autotuning has been shown to achieve better or more portable performance in a
number of domains. However, autotuners themselves are rarely portable between projects …

FFTW is an implementation of the discrete Fourier transform (DFT) that adapts to the
hardware in order to maximize performance. This paper shows that such an approach can …

While computer-aided design is a major part of many modern manufacturing pipelines, the
design files typically generated describe raw geometry. Lost in this representation is the …

Fast changing, increasingly complex, and diverse computing platforms pose central
problems in scientific computing: How to achieve, with reasonable effort, portable optimal …

In this paper, we present some of the challenges and opportunities in software development
based on the current hardware trends and the impact of massive parallelism on both the …

Software engineering demands generality and abstraction, performance demands
specialization and concretization. Generative programming can provide both, but the effort …

This paper introduces the concept of programming with sketches, an approach for the rapid
development of high-performance applications. This approach allows a programmer to write …

Computing systems are becoming increasingly parallel and heterogeneous, and therefore
new applications must be capable of exploiting parallelism in order to continue achieving …

As parallel applications become more complex, auto-tuning becomes more desirable,
challenging, and time-consuming. We propose, Bliss, a novel solution for auto-tuning …